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In this observational study, using the Global Burden of Disease and Risk Factors Study, we aimed to (i) report the magnitude of health loss due to non-communicable neurological disorders in the USA in 2017 by sex, age, years and States and (ii) to identify non-communicable neurological disorders attributable environmental, metabolic and behavioural risk factors. We provide estimates of the burden of non-communicable neurological disorders by reporting disability-adjusted life-years and their trends from 1990 to 2017 by age and sex in the USA. The non-communicable neurological disorders include migraines, tension-type headaches, multiple sclerosis, Alzheimer's disease and other dementias, Parkinson's disease, epilepsy, motor neuron diseases and other neurological disorders. In 2017, the global burdens of non-communicable neurological disorders were 1444.41 per 100 000, compared to the USA burden of 1574.0. Migraine was the leading age-standardized disability-adjusted life-years 704.7 per 100 000, with Alzheimer's disease and other dementias (41.8.7), and epilepsy (123.8) taking the second and third places, respectively. Between 1990 and 2017, the age-standardized disability-adjusted life-years rates for aggregate non-communicable neurological disorders relative to all cause increased by 3.42%. More specifically, this value for motor neuron diseases, Parkinson's disease and multiple sclerosis increase by 20.9%, 4.0%, 2.47%, 3.0% and 1.65%, respectively. In 2017, the age-standardized disability-adjusted life-years rates for the aggregate non-communicable neurological disorders was significantly higher in females than the males (1843.5 versus 1297.3 per 100 000), respectively. The age-standardized disability-adjusted life-years rates for migraine were the largest in both females (968.8) and males were (432.5) compared to other individual non-communicable neurological disorders. In the same year, the leading non-communicable neurological disorders age-standardized disability-adjusted life-years rates among children ≤9 was epilepsy (216.4 per 100 000). Among the adults aged 35-60 years, it was migraine (5792.0 per 100 000), and among the aged 65 and above was Alzheimer's disease and other dementias (78 800.1 per 100 000). High body mass index, smoking, high fasting plasma glaucous and alcohol use were the attributable age-standardized disability-adjusted life-years risks for aggregate and individual non-communicable neurological disorders. Despite efforts to decrease the burden of non-communicable neurological disorders in the USA, they continue to burden the health of the population. Children are most vulnerable to epilepsy-related health burden, adolescents and young adults to migraine, and elderly to Alzheimer's disease and other dementias and epilepsy. In all, the most vulnerable populations to non-communicable neurological disorders are females, young adults and the elderly.
Learning to predict threatening events enables an organism to engage in protective behavior and prevent harm. Failure to differentiate between cues that truly predict danger and those that do not, however, may lead to indiscriminate fear and avoidance behaviors, which in turn may contribute to disability in people with persistent pain. We aimed to test whether people with persistent neck pain exhibit contingency learning deficits in predicting pain relative to pain-free, gender-and age-matched controls.
Endometriosis is a systemic and chronic condition in women of childbearing age, yet a highly enigmatic disease with unresolved questions: there are no known biomarkers, nor established clinical stages. We here investigate the use of patient-generated health data and data-driven phenotyping to characterize endometriosis patient subtypes, based on their reported signs and symptoms. We aim at unsupervised learning of endometriosis phenotypes using self-tracking data from personal smartphones. We leverage data from an observational research study of over 4000 women with endometriosis that track their condition over more than 2 years. We extend a classical mixed-membership model to accommodate the idiosyncrasies of the data at hand, i.e., the multimodality and uncertainty of the self-tracked variables. The proposed method, by jointly modeling a wide range of observations (i.e., participant symptoms, quality of life, treatments), identifies clinically relevant endometriosis subtypes. Experiments show that our method is robust to different hyperparameter choices and the biases of self-tracking data (e.g., the wide variations in tracking frequency among participants). With this work, we show the promise of unsupervised learning of endometriosis subtypes from self-tracked data, as learned phenotypes align well with what is already known about the disease, but also suggest new clinically actionable findings. More generally, we argue that a continued research effort on unsupervised phenotyping methods with patient-generated health data via new mobile and digital technologies will have significant impact on the study of enigmatic diseases in particular, and health in general.
Sex differences in pain sensitivity have been well documented, such that women often report greater sensitivity than men. However, clinical reports highlighting sex differences often equate gender and sex. This is a particularly critical oversight for those whose gender identity is different than their genetic sex.
To explore the efficacy of cathodal tDCS applied ipsilateral to the cold patch, as determined by thermographic evaluation, in the treatment of chronic migraine. Transcranial direct current stimulation (tDCS) is a non-invasive and safe technique that modulates the activity of the underlying cerebral cortex. tDCS has been extensively tested as a possible treatment for chronic pain and migraine with controversial results mainly due to the different setting procedure and location of electrodes. Since the presence of a hypothermic patch region detected through thermography has been suggested as a possible support for headache diagnosis, this "cold patch" could considered as possible effective location for tDCS application. Forty-five patients with chronic migraine were randomized to receive either cathodal (25 patients) or sham tDCS, for 5 consecutive daily sessions plus a recall session after 1 month. Cathodal tDCS was delivered at 1.5 mA for 15 min in each session. Subjects were evaluated before treatment (baseline, T0), and after 10 (T10), 60 (T60), and 120 (T120) days after treatment. The number of attacks, duration of attacks, pain intensity, number of days with headache, and number of analgesics were collected at each time evaluation. Patients in the tDCS group showed a significant improvement compared to the sham group, during the whole study period in the frequency of migraine attacks (tDCS vs. sham: -47.8 ± 50.1% vs. -14.2 ± 16.5%, = 0.004), number of days with headache (tDCS vs. sham: -42.7 ± 65.4% vs. -11.3 ± 18.0%, = 0.015), duration of attacks (tDCS vs. sham: -29.1 ± 43.4% vs. -7.5 ± 17.6%, = 0.016), intensity of the pain during an attack (tDCS vs. sham -31.1 ± 36.9% vs. 8.3 ± 13.5%, = 0.004), and number of analgesics (tDCS vs. sham -54.3 ± 37.4% vs. -16.0 ± 19.6%, < 0.0001). Our results suggest that cathodal tDCS is an effective adjuvant technique in migraine provided that an individual correct montage of the electrodes is applied, according to thermographic investigation.
Referral to secondary care is common for a considerable proportion of patients with persistent sciatica symptoms. It is unclear if information from clinical assessment can further identify distinct subgroups of disc-related sciatica, with perhaps different clinical courses.
Distraction is a well-established pain management technique for children experiencing acute pain, although the mechanisms underlying the effectiveness of distraction are not well understood. It has been postulated that engagement of executive functions, such as working memory, may be a critical factor in attenuating pain via distraction. To test this hypothesis, we compared a 1-back task requiring engagement of working memory with a simple visual discrimination task demanding focused attention, but lower cognitive load (0-back).
Coping strategies and their efficacy vary greatly in patients suffering from fibromyalgia syndrome (FMS).
Novel suggestions derived from the inhibitory learning model on how to optimize exposure therapy have been debated with enthusiasm in the last few years, particularly with respect to the focus on expectancy violations. However, little is known about how this new approach directly compares to the traditional habituation rationale of exposure therapy. In the present study, we examined these two competing therapeutic instructions among healthy female participants in an experimental heat pain paradigm.
Fibromyalgia (FM) is a frequent comorbidity in patients with chronic migraine (CM). PREEMPT trials, which demonstrated the efficacy of OnabotulinumtoxinA (OnabotA) on CM, excluded patients with FM. Our aim was to evaluate the effectiveness of OnabotA in a series of patients with CM and FM. We analyzed patients with a previous diagnosis of CM and FM who had received sessions of OnabotA quarterly between January 2014 and January 2020 in a specialized Headache Clinic. Primary endpoint was the reduction in moderate to severe headache days at 3, 6, 9, and 12 months. Data were collected from 31 patients with CM and FM that received OnabotA (100% females). Mean age at first procedure was 50.2 ± 11.3 years. Depression (93.5%), other central sensitization syndromes (irritable bowel syndrome, interstitial cystitis, multiple chemical sensitivity, endometriosis, and chronic fatigue syndrome) (48.4%), and medication overuse headache (90.3%) were frequent comorbidities. 48.4% of patients had failed ≥3 preventives previously. The percentage of patients who achieved ≥30 and ≥50% moderate-severe headache reduction on the third month was 65.4 and 48.2%, respectively. Twenty-three patients completed four cycles of treatment, with 13.4 fewer headache days per month than at baseline ( < 0.001). By 1 year, 69.5% had ≥50% reduction of headache frequency and 39.1% had a ≥75% reduction. In 4 cases (21%), OnabotA was interrupted due to a lack of response. Only mild adverse effects were recorded. OnabotA is an effective treatment for CM in patients with FM.